Collaborative programming is an effective approach to software development, improving software quality, programmer's satisfaction and shortening delivery time. This study examines the application of a collaborative Web-based IDE named IDEOL to execute a four-week multi-submission programming assignment in an introductory object-oriented programming class. Forty eight students forming 24 two-member groups in class used the IDE to interact and write source code required by the project. All collaborative and programming activities performed by students were recorded by IDEOL. The results of the study shows that students tend to postpone their programming work until the submission dates. This study also provides an approach to designing and executing an extended programming exercises, which receives high student satisfaction. Our results imply that IDEOL is a useful environment for students to collaborate, learn, and practice programming to improve their learning satisfaction.In addition, as students tend to procrastinate, IDEOL is a useful tool to facilitate, monitor, and report student progress in extended programming exercises.
There have been studies suggesting that collaboration and cooperation can deliver higher performance than competition or individual work. The Web does not only provide ubiquitous access to resources and computation power but also can be an open structure for better and continuous collaboration. In this study, we introduce our vision and construction of an integrated social environment called EduCo to assist teaching and learning software engineering courses. EduCo is a Web environment for instructors to teach and for students to learn and practice designing, programming, and managing software in software engineering courses. It is also a social network platform that helps stimulate participation, interaction, sharing, awareness, accountability, and teamwork. This paper describes the initial construction of the system with many core capabilities realized. The paper also presents our case studies from applying the system to several programming language classes. The results from the case studies suggest that the system has the potential to encourage students' participation and satisfaction. In addition, this paper presents our vision for future enhancements of the system with core capabilities such as feeds, dashboards, notifications, tracking, and reporting.
Many spreadsheets in the wild do not have documentation nor categorization associated with them. This makes difficult to apply spreadsheet research that targets specific spreadsheet domains such as financial or database. We introduce with this paper a methodology to automatically classify spreadsheets into different domains. We exploit existing data mining classification algorithms using spreadsheet-specific features. The algorithms were trained and validated with cross-validation using the EUSES corpus, with an up to 89% accuracy. The best algorithm was applied to the larger Enron corpus in order to get some insight from it and to demonstrate the usefulness of this work.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.